In this paper, we consider optimal market timing strategies under transaction costs. We assume that the asset's return follows an ARMA (1, 1) model and use long-term investment growth as the objective of a market timing strategy which entails the shifting of funds between a risky asset and a riskless asset. By the use of stochastic dynamic programming techniques, we derive the optimal trading strategies for finite investment horizon, and analyze its limiting behavior. For finite horizon, the optimal decision in each step depends on two control variables. When investment horizon tends to infinity, we prove that the optimal strategy converges to a stationary policy, which also depends on two control variables. An integral equation of the two control variables is given. Numerical solutions and average returns associated with the limiting stationary strategy are also presented. Numerical results confirm that the no-transaction region increases as the transaction cost increases. Finally, the limiting stationary strategy is simulated using data in the Hang Seng Index Futures market in Hong Kong. The out-of-sample performance of the limiting stationary strategy is found to be comparable to that of a buy-and-hold strategy.
|Title of host publication||Advances in Investment Analysis and Portfolio Management. Volume 7|
|Number of pages||28|
|Publication status||Published - 20 Dec 2000|